Abstract
Advances in the Internet of Things and the Web of Data created huge opportunities for developing applications that can generate actionable knowledge out of streaming data. The trade-off between scalability and expressivity is a key challenge in this setting, and more investigation is required to identify what are the relevant features in optimizing this trade-off, and what role do they have in the optimization. In this paper we motivate the need for heuristics to design adaptive solutions and, following an empirical approach, we highlight some key concepts and ideas that can guide the design of heuristics for adaptive optimization of Web Stream Reasoning.
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Notes
- 1.
Note that in ASP, the expressivity of the language is strictly related to the computational complexity, therefore we refer to expressivity and (computational) complexity interchangeably throughout the paper.
- 2.
In this paper we only consider non-overlapping windows. For overlapping windows, the formula \( T_\omega (S, W) \) should hold also when duplicating events in overlapping parts.
- 3.
Note that this is different from the total processing time, which includes the time required for query processing (first tier). In this paper, we mainly focus on the reasoning time only, relying on the extensive evaluation of query processing engines for the query processing time [1].
- 4.
Note that this is different from the streaming size.
- 5.
In the current implementation we evaluate criticality mainly based on how close an event is to the user location, and how fast is the user moving. In future work we plan to extend this contextual characterization to consider not only location but also other features such as the user transportation type, user’s health condition etc.
- 6.
Algorithms to perform such splits are under investigation and will be the subject of future work.
- 7.
Note that our goal is not to find the minimum, we just want to find one split.
- 8.
Note that this assumption needs to be formally characterized and more investigation is ongoing in this direction.
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Acknowledgments
This research has been partially supported by Science Foundation Ireland (SFI) under grant No. SFI/12/RC/2289 and EU FP7 CityPulse Project under grant No.603095. http://www.ict-citypulse.eu
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Germano, S., Pham, TL., Mileo, A. (2015). Web Stream Reasoning in Practice: On the Expressivity vs. Scalability Tradeoff. In: ten Cate, B., Mileo, A. (eds) Web Reasoning and Rule Systems. RR 2015. Lecture Notes in Computer Science(), vol 9209. Springer, Cham. https://doi.org/10.1007/978-3-319-22002-4_9
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